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Jianguo Li

14 papers hereh-index 279k citations61 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author10
  • last author3

Across the 14 of 14 papers where every author was matched, so the position is known.

fields
  • cs.CV13
  • cs.LG1
same name
  • Jianguo Li — 19 papers, h 13
  • Jianguo Li — 18 papers, h 7
  • Jianguo Li — 7 papers, h 37
  • Jianguo Li — 7 papers, h 3
  • Jianguo Li — 6 papers, h 5
  • Jianguo Li — 4 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20142021
most citedLearning Efficient Convolutional Networks through Network Slimming

270 citations · 805 across the 14 of their papers we have counts for

collaborators
Showing 2018 · cs.CVShow all

4 papers · 2 filters

cs.CV2018★ 2 cited

Object Detection from Scratch with Deep Supervision

Zhiqiang Shen, Zhuang Liu, Jianguo Li +3

We propose Deeply Supervised Object Detectors (DSOD), an object detection framework that can be trained from scratch. Recent advances in object detection heavily depend on the off-…

cs.CV2018★ 77 cited

Network Decoupling: From Regular to Depthwise Separable Convolutions

Jianbo Guo, Yuxi Li, Weiyao Lin +2

Depthwise separable convolution has shown great efficiency in network design, but requires time-consuming training procedure with full training-set available. This paper first anal…

cs.CV2018★ 101 cited

Tiny-DSOD: Lightweight Object Detection for Resource-Restricted Usages

Yuxi Li, Jiuwei Li, Weiyao Lin +1

Object detection has made great progress in the past few years along with the development of deep learning. However, most current object detection methods are resource hungry, whic…

cs.CV2018★ 14 cited

Learning Visual Knowledge Memory Networks for Visual Question Answering

Zhou Su, Chen Zhu, Yinpeng Dong +3

Visual question answering (VQA) requires joint comprehension of images and natural language questions, where many questions can't be directly or clearly answered from visual conten…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.